README.md

Introduction

This is an examle of how to setup instance on floydhub to run lesson 1 of the awesome deep learning course available at http://course.fast.ai/. This document was revised March 5th 2017 and now works with the full dogscats dataset.

data

I copied the dogscats sample dataset (dogscats/sample if you unzip the dogscats.zip at http://files.fast.ai/data/dogscats.zip). However, this is considered very bad practice, because I am creating a copy of the data every time I start a new cloud instance. Please refer to the bottom section "Run for the full dogs and cats dataset" for data preperation best practice.

dependencies

The scripts written in lesson 1 runs with python 2 + Keras + Theano, so you need to specify --env theano:py2 when you start the cloud instance (more details below). However, Floydnet theano:py2 environment is still missing one package - bcolz. For this, you need to add it to file "floyd_requirements.txt". This is the floydnet default for installing dependencies.

echo "bcolz" > floyd_requirements.txt

Start a floydnet instance

We will use Floyd CLI to initiate a cloud instance. Initiation:

floyd init your_favorate_task_name_e.g._neural_networks

To start a GPU instance with Jupyter notebook that is compatable to lesson 1 scripts, you need to specify the following parameters:

floyd run \
--mode jupyter \
--env theano:py2 \
--gpu

Wait for a few minutes, then you should get a website address in your console for the running Jupyter notebook.

One more thing before running lesson 1 code

We are almost there, but there is one more thing we need to configure - the keras.json file

the mounted data is available in /input/ directory, and you need to direct the unzipped files to /output/ directory

After this finishes, which took about 20 mins for me, you'll see in your floydhub UI interface, under "Data" section, a dataset userID/dogscats.unzip:1/output. On the right side, click View -> Advanced -> under Id, keep a record of your data Id. Mine is yz3A8G5vX5ZQxv5VVyD3GH

Now, we are ready to create the actual floydnet workspace to start learning fast.ai!
Assuming you have cloned this repo following the method running sample dataset.